A central paradigm of medical genetics is that the phenotype of a deletion syndrome results from the disruption of the deleted genes themselves. In direct contradistinction to this dogma, we propose that genetic diseases can be caused or modified by changes in physical, long-range interactions that normally occur between loci that are now deleted and genes that are far from the deleted region when plotted on a linear genetic map. In contrast to focusing on singe deletion-candidate gene interaction, though, we propose that a network of co- regulated genes physically co-localizes, and that phenotypic variation results from the combinatorial disruption of different spokes of this chromatin hub in different individuals. Since deletion syndromes are often characterized by multiple phenotypes, we will test our hypothesis on the most common genomic deletion disorder, deletion of human 22q11 (del22q11), which is characterized by remarkable phenotypic variation. del22q11 may be the most common genetic risk factor for schizophrenia. We have identified a hub of 13 genes on 8 chromosomes that physically interacts with 22q11. We will study DNA and RNA samples from fully phenotyped patients who harbor the deletion, as well as cell lines from normal and affected patients. 1) Using the Associated Chromosome Trap assay, our recently published novel methodology for discovering long-range chromatin interactions, we will identify all genes that physically interact with the commonly deleted region of 22q11. 2) We will confirm that these interactions occur in healthy individuals using fluorescent in situ hybridization and the high-resolution molecular assay chromosome conformation capture. 3) We can then use this catalog of associated genes to examine their potential roles in disease manifestation. 4) We will use knock-out mice to confirm the role of the genes in this hub in cardiac development and disease. This proposal is high-risk because we aim to focus on the physical network itself, rather than the high-yield disease-causing genes that compose those networks. The impact of this hypothesis will extend beyond genetic syndromes to chromosomal rearrangements in cancers, and it will uncover and explain genetic risks for complex diseases.